Chip startups using light instead of wires gain momentum and investment By Reuters


© Reuters. A display of a PsiQuantum Wafer, a silicon wafer containing thousands of quantum devices, including single-photon detectors, manufactured through PsiQuantum’s partnership with GlobalFoundries in Palo Alto, California, USA, in an undated image taken in March 202


By Jane Lanhee Lee

(Reuters) – Computers that use light rather than electric currents for processing, only years ago seen as research projects, are gaining ground, and startups that have solved the technical challenge of using photons in chips are getting big bucks.

In the latest example, Ayar Labs, a startup developing this technology called silicon photonics, said on Tuesday that it had raised $ 130 million from investors, including chip giant Nvidia (NASDAQ 🙂 Corp.

While the transistor-based silicon chip has increased its computing power exponentially over the past few decades, as transistors have reached the width of several atoms, it is a challenge to shrink them further. Not only is it difficult to do something so minimal, but as they get smaller, the signals can soften between them.

So Moore’s law, which said that the density of transistors on a chip would double every two years and reduce costs, is slowing down, forcing industry to seek new solutions to deal with increasingly heavy computing needs with artificial intelligence.

According to data company PitchBook, silicon photonics startups raised over $ 750 million last year, a doubling from 2020. In 2016, it was around $ 18 million.

“AI is growing like crazy and taking over large parts of the data center,” Ayar Labs CEO Charles Wuischpard told Reuters in an interview. “The data movement challenge and the energy consumption of that data movement is a big, big problem.”

The challenge is that many large machine learning algorithms can use hundreds or thousands of chips for computers, and there is a bottleneck in the speed of data transmission between chips or servers using current electrical methods.

Light has been used to transmit data through fiber optic cables, including subsea cables, for decades, but it was difficult to bring it to chip level, as devices used to create light or control it have not been so easy to shrink like transistors.

PitchBooks senior new technology analyst Brendan Burke expects silicon photonics to become commonplace in data centers by 2025 and estimates the market will reach $ 3 billion by the time, equivalent to the market size of the AI ​​graphics chip market by 2020.

In addition to connecting transistor chips, startups that use silicon photonics to build quantum computers, supercomputers, and chips for self-driving vehicles also raise large funds.

PsiQuantum raised about $ 665 million so far, although the promise of quantum computers changing the world is still years away.

Lightmatter, which builds processors that use light to accelerate the AI ​​workload in the data center, raised a total of $ 113 million and will release its chips later this year and test with customers shortly after.

Luminous Computing, a startup building an AI supercomputer using silicon photonics backed by Bill Gates, raised a total of $ 115 million.


It is not just startups that are pushing this technology forward. Semiconductor manufacturers are also preparing to use their technology to make silicon chips for photonics.

GlobalFoundries Head of Computing and Wired Infrastructure Amir Faintuch said the collaboration with PsiQuantum, Ayar and Lightmatter has helped build a silicon photonics production platform that others can use. The platform was launched in March.

Peter Barrett, founder of venture capital firm Playground Global, an investor in Ayar Labs and PsiQuantum, believes in the long-term prospects of silicon photonics to accelerate data processing, but says it is a long way off.

“What the Ayar Labs guys are doing so well … is that they solved the data connectivity problem of traditional high-performance (computing),” he said. “But it will be a while before we have pure digital photonic computing for non-quantum systems.”

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